Use Time Series to Generate and Compare Power Spectral Density

---

Documentation for package ‘psdr’ version 1.0.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

AutomatedCompositePlotting	Automated plotting of time series, PSD, and log transformed PSD
CountWindows	Create a contingency table to display how many windows (dataframes) fall into particular categories
FindHomogeneousWindows	Assess if window (dataframe) share certain features across all observations
GenerateExampleData	Produce example data set for demonstrating package functions
GetHomogeneousWindows	Get windows (dataframes) that have the same specified column values for all observations
GetSubsetOfWindows	Select only windows (dataframes) where a specified column matches a specified value
GetSubsetOfWindowsTwoLevels	Select only windows (dataframes) where a two specified columns must match specified values
IdentifyMaxOnXY	Given a xy plot. Find the maximum value on the plot
MakeCompositePSDForAllWindows	Make PSD for each window (dataframe) in a list and then find the average of all the PSDs
MakeCompositeXYPlotForAllWindows	Find averaged xy plots
MakeOneSidedAmplitudeSpectrum	Create a one sided amplitude spectrum using time series data
MakePowerSpectralDensity	Create a power spectral density (PSD) plot using time series data
PSDDominantFrequencyForMultipleWindows	Calculate dominant frequency for multiple PSDs for a single frequency range
PSDIdentifyDominantFrequency	Given a time series vector, create a PSD and find the dominant frequency
PSDIntegrationPerFreqBin	Given a time series vector, generate a PSD, then calculate integration for specified bins
SingleBinPSDIntegrationForMultipleWindows	Calculate integral for multiple PSDs for a single frequency bin
SingleBinPSDIntegrationOrDominantFreqComparison	Given sets of windows (dataframes) corresponding to different combos, see if the integration or dominant frequency of a specific frequency range is significantly different between the combos